A Complex Adaptive E-Learning Model Based on Semantic Web Services

Nowadays, adaptive e-learning systems are responsible for selecting learning materials or contents according to the learners´ style, profile, interest, previous knowledge level, goal, pedagogical method etc to provide highly personalized learning sessions. Complex adaptive system (CAS) method lays stress on adaptation and positive feedbacks. And semantic Web service aims at giving information a well-defined meaning, enabling computers and people to work in cooperation better through the definition of ontologies. This paper presents a complex adaptive e-learning model based on semantic Web services. It overviews the basic concepts of CAS method and semantic Web service firstly. Then the framework of complex adaptive e-learning model is illustrated, and how to realize the adaptation in this model based on complex adaptive model and semantic Web service are described secondly. Through the CAS method, a user can discover the suitable e-learning resources according to his/hers preference and constrain. Conclusions are given finally.